• Management Science and Financial Engineering
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• v.19 no.1
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• pp.25-28
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• 2013

Consider the inverse bin-packing number problem. Given a set of items and a prescribed number K of bins, the inverse bin-packing number problem, IBPN for short, is concerned with determining the minimum perturbation to the item-size vector so that all the items can be packed into K bins or less. It is known that this problem is NP-hard (Chung, 2012). In this paper, we investigate some special cases of IBPN that can be solved in polynomial time. We propose an optimal algorithm for solving the IBPN instances with two distinct item sizes and the instances with large items.

• Journal of the Korean Chemical Society
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• v.57 no.2
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• pp.172-175
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• 2013

We compare the relative usefulness of common basis functions and numerical integration methods in representing complex resonance state encountered in the molecular scattering problem of aluminum dimer electronic predissociation. Specifically, the basis set size and computing CPU times are monitored in order to find the minimum requirement for ensuring the modest accuracy of calculated resonance energies (0.1 $cm^{-1}$) for more than 100 resonance states. The combination of the so-called one-dimensional box eigenfunctions and energy-dependent boundary functions are found to be most efficient if integration is done using the basis set quadrature rules.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.13-24
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• 2001

In this paper, we investigated mean estimation methods in two-phase sampling. Under the fixed expected cost we reviewed the optimal sample sizes, minimum variances and approximate unbiased variance estimators for usual ratio estimator, stratified sample mean with proportional allocation and Rao's allocation of the second phase sample. Also we proposed combined ratio estimator, which uses both ratio estimation and stratification and derived optimal sample size, minimum variance and unbiased variance estimator. Through a limited simulation study, we compared estimators by design effects and came to know that ratio estimator is more efficient than stratified sample mean in some cases and inefficient in the other cases, but combined ratio estimator is more efficient than others in most cases.

• Korean Journal of Veterinary Research
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• v.48 no.4
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• pp.457-462
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• 2008

The objective of this study was to determine appropriate sample size that simulated different assumptions for diagnostic test characteristics and true prevalences when designing serological surveillance plan for pullorum disease and fowl typhoid in domestic poultry production. The number of flocks and total number of chickens to be sampled was obtained to provide 95% confidence of detecting at least one infected flock, taking imperfect diagnostic tests into account. Due to lack of reliable data, within infected flock prevalence (WFP) was assumed to follow minimum 1%, most likely 5% and maximum 9% and true flock prevalence of 0.1%, 0.5% and 1% in order. Sensitivity were modeled using the Pert distribution: minimum 75%, most likely 80% and maximum 90% for plate agglutination test and 80%, 85%, and 90% for ELISA test. Similarly, the specificity was modeled 85%, 90%, 95% for plate agglutination test and 90%, 95%, 99% for ELISA test. In accordance with the current regulation, flock-level test characteristics calculated assuming that 30 samples are taken from per flock. The model showed that the current 112,000 annual number of testing plan which is based on random selection of flocks is far beyond the sample size estimated in this study. The sample size was further reduced with increased sensitivity and specificity of the test and decreased WFP. The effect of increasing samples per flock on total sample size to be sampled and optimal combination of sensitivity and specificity of the test for the purpose of the surveillance is discussed regarding cost.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.709-717
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• 1997

For an undirected graph G=(V, E), the Rural Postman Problem (RPP) is a problem that finds a minimum cost tour that must pass edges in E'($\subseteq$ E) at least once. RPP, such as Traveling Salesman Problem (TSP), is known as an NP. Complete problem. In the previous study of RPP, he structure of the chromosome is constructed by E' and the direction of the edge. Hence, the larger the size of IE' I is, the larger the size of the chromosome and the size of the solution space are. In this paper, we transform the RPP into a Hamiltonian graph and use a genetic algorithm to solve the transformed problem using restructured chromosomes. In the simulations, we analyze our method and the previous study. From the simulation results, it is found that the results of the proposed method is better than those of the previous method and the proposed method also obtains the near optimal solution in earlier generations than the previous study.

• Journal of Korean Society of Transportation
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• v.35 no.1
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• pp.63-78
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• 2017

The purpose of this study is to determine the optimal aggregation interval to increase the reliability when estimating representative value of individual vehicle travel time collected by DSRC equipment in interrupted traffic flow section in National Highway. For this, we use the bimodal asymmetric distribution data, which is the distribution of the most representative individual vehicle travel time collected in the interrupted traffic flow section, and estimate the MSE(Mean Square Error) according to the variation of the aggregation interval of individual vehicle travel time, and determine the optimal aggregation interval. The estimation equation for the MSE estimation utilizes the maximum estimation error equation of t-distribution that can be used in asymmetric distribution. For the analysis of optimal aggregation interval size, the aggregation interval size of individual vehicle travel time was only 3 minutes or more apart from the aggregation interval size of 1-2 minutes in which the collection of data was normally lost due to the signal stop in the interrupted traffic flow section. The aggregation interval that causes the missing part in the data collection causes another error in the missing data correction process and is excluded. As a result, the optimal aggregation interval for the minimum MSE was 3~5 minutes. Considering both the efficiency of the system operation and the improvement of the reliability of calculation of the travel time, it is effective to operate the basic aggregation interval as 5 minutes as usual and to reduce the aggregation interval to 3 minutes in case of congestion.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.27-43
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• 1978

This paper deals with the problem of obtaining a minimum cost acceptance sampling plan for destructive testing. The cost model is constructed under the assumption that the sampling procedure takes the following form; 1) lots rejected on the first sample are acreened with a non-destructive testing, 2) the screening is assumed to be imperfect, and therefore, after the screening, a second sample is taken to determine whether to accept the lot of to scrap it. The usual sampling procedures for destructive testing can be regarded as special cases of the above one. Utilizing Hald's Bayesian approach, procedures for finding the global optimal sampling plans are given. However, when the lot size is large, the global plan is very different to obtain even with the aid of an electronic computer. Therefore a method of finding suboptimal plan is suggested. An example with uniform prior is also given.

• Journal of the Korean Institute of Gas
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• v.4 no.2 s.10
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• pp.7-14
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• 2000

LNG (Liquified Natural Gas) carried by LNG ship is unloaded into the LNG storage tanks at the very low temperature (a little lower than the boiling point of LNG). Because LNG is unloaded through the pipeline, two phase flow appears in the pipeline. In this study, we have studied the pressure-drop mechanisms of the two-phase flow in the pipeline, and the calculation method of BOG (Boil-off Gas) amount based on the heat transfer mechanism through the insulation and the surface of the pipeline. We have developed a computer program for thermal-hydraulic analysis on the LNG pipeline system. We have also developed the optimal design program to find the optimal thickness of insulation and the pipeline size. The program searches the optimal design with the minimum capital cost of pipelines and insulation on the operating conditions of maximum allowance pressure-drop and BOG amount, etc.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.105-111
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• 2024

This paper deals with the minimum linear arrangement(MinLA) of a lattice graph, to which an approximate algorithm of linear complexity O(n) remains as a viable solution, deriving the optimal MinLA of 31,680 for 33×33 lattice. This paper proposes a partitioning arrangement algorithm of complexity O(1) that delivers exact solution to the minimum linear arrangement. The proposed partitioning arrangement algorithm could be seen as loading boxes into a container. It firstly partitions m rows into r₁,r₂,r₃ and n columns into c₁,c₂,c₃, only to obtain 7 containers. Containers are partitioning with a rule. It finally assigns numbers to vertices in each of the partitioned boxes location-wise so as to obtain the MinLA. Given m,n≥11, the size of boxes C₂,C₄,C₆ is increased by 2 until an increase in the MinLA is detected. This process repeats itself 4 times at maximum given m,n≤100. When tested to lattice in the range of 2≤n≤100, the proposed algorithm has proved its universal applicability to lattices of both m=n and m≠n. It has also obtained optimal results for 33×33 and 100×100 lattices superior to those obtained by existing algorithms. The minimum linear arrangement algorithm proposed in this paper, with its simplicity and outstanding performance, could therefore be also applied to the field of Very Large Scale Integration circuit where m,n are infinitely large.